Abstract: A dosimetry assessment method for an organ at risk (OAR) in an esophageal radiotherapy plan includes: acquiring volumetric-modulated arc therapy (VMAT) plan data of a patient with esophageal cancer, and obtaining a distance-target histogram (DTH); subjecting a geometric feature vector of the DTH to dimension reduction to obtain a dimension-reduced geometric feature vector; establishing a deep belief network (DBN) model, and completing training the DBN model; non-linearly fitting a correlation between a dose feature vector and the dimension-reduced geometric feature vector to obtain a dose feature vector with a dimension being identical to a dimension of the dimension-reduced geometric feature vector; and reconstructing the dose feature vector through a decoding layer of an autoencoder structure to obtain a dose feature vector with a dimension being identical to a dimension of the geometric feature vector before the dimension reduction, and finally obtaining a dose-volume histogram (DVH) for predicting the OAR

Abstract: Provided is a method of detecting free mannose and glucose in serum using high performance liquid chromatography. Compared to existing technology, the pretreatment process of samples is simpler, the detection time is shortened, and the detection efficiency is greater. When detection of serum samples is carried out, mannose, rhamnose and glucose may be completely separated, and mannose and glucose will not affect each other during quantification, thereby ensuring the accuracy of detection results.